Models of integration given multiple sources of information.

Abstract

Several models of information integration are developed and analyzed within the context of a proto-typical pattern-recognition task. The central concerns are whether the models prescribe maximally efficient (optimal) integration and to what extent the models are psychologically valid. Evaluation, integration, and decision processes are specified for each model. Important features are whether evaluation is noisy, whether integration follows Bayes's theorem, and whether decision consists of a criterion rule or a relative goodness rule. Simulations of the models and predictions of the results by the same models are carried out to provide a measure of identifiability or the extent to which the models can be distinguished from one another. The models are also contrasted against empirical results from tasks with 2 and 4 response alternatives and with graded responses.